Voldemort does not try to satisfy arbitrary relations and the ACID properties, but rather is a big, distributed, persistent hash table.[2] A 2012 study comparing systems for storing application performance management data reported that Voldemort, Apache Cassandra, and HBase all offered linear scalability in most cases, with Voldemort having the lowest latency and Cassandra having the highest throughput.[3]
In the parlance of Eric Brewer's CAP theorem, Voldemort is an AP type system.
Voldemort's creator and primary corporate contributor, LinkedIn, has migrated all of their systems off of Voldemort as of approximately August 2018, with no replacement sponsor as of October 2018[update].[4]
Properties
Voldemort uses in-memory caching to eliminate a separate caching tier. It has a storage layer that is possible to emulate. Voldemort reads and writes scale horizontally. The API decides data replication and placement and accommodates a wide range of application-specific strategies.[2][5]
The Voldemort distributed data store supports pluggable placement strategies for distribution across data centers. Data is automatically replicated across servers. Data is partitioned meaning a single server contains only a portion of the total data. Each data node is independent to avoid central point of failure. Pluggable serialization allows rich keys and values including lists and tuples with named fields, as well as the integration with common serialisation frameworks such as Avro, Java Serialization, Protocol Buffers, and Thrift. Server failures are handled transparently. Data items are versioned, which maximizes data integrity.[1]
^ ab"Voldemort is a distributed key-value storage system". Project Voldemort - A distributed database. Retrieved 2015-04-20.
^ ab. Project Voldemort - A distributed database. Archived from the original on 2011-04-23. Retrieved 2011-04-05.
^Rabl, Tilmann; Sadoghi, Mohammad; Jacobsen, Hans-Arno; Gómez-Villamor, Sergio; Muntés-Mulero, Victor; Mankovskii, Serge (August 2012). "Solving Big Data Challenges for Enterprise Application Performance Management" (PDF). Proceedings of the VLDB Endowment. 5 (12): 1724–1735. arXiv:1208.4167. doi:10.14778/2367502.2367512. S2CID 15591565.
^project-voldemort mailing list post. 2018-08-16. Retrieved 2018-10-06.
^Serving Large-scale Batch Computed Data with Project Voldemort
External links
Project Voldemort - A distributed database
Project Voldemort Real Time Discussions
January 19, 2023
voldemort, distributed, data, store, voldemort, distributed, data, store, that, designed, value, store, used, linkedin, highly, scalable, storage, named, after, fictional, harry, potter, villain, lord, voldemort, project, voldemortoriginal, author, linkedin, m. Voldemort is a distributed data store that was designed as a key value store used by LinkedIn for highly scalable storage 1 It is named after the fictional Harry Potter villain Lord Voldemort Project VoldemortOriginal author s LinkedIn MicrosoftInitial release2009 14 years ago 2009 Stable release1 10 25 July 25 2017 5 years ago 2017 07 25 Repositorygithub wbr com wbr voldemort wbr voldemortWritten inJavaAvailable inEnglishTypeDistributed data storeLicenseApache License 2 0Websitewww wbr project voldemort wbr com Contents 1 Overview 2 Properties 3 See also 4 References 5 External linksOverview EditVoldemort does not try to satisfy arbitrary relations and the ACID properties but rather is a big distributed persistent hash table 2 A 2012 study comparing systems for storing application performance management data reported that Voldemort Apache Cassandra and HBase all offered linear scalability in most cases with Voldemort having the lowest latency and Cassandra having the highest throughput 3 In the parlance of Eric Brewer s CAP theorem Voldemort is an AP type system Voldemort s creator and primary corporate contributor LinkedIn has migrated all of their systems off of Voldemort as of approximately August 2018 with no replacement sponsor as of October 2018 update 4 Properties EditVoldemort uses in memory caching to eliminate a separate caching tier It has a storage layer that is possible to emulate Voldemort reads and writes scale horizontally The API decides data replication and placement and accommodates a wide range of application specific strategies 2 5 The Voldemort distributed data store supports pluggable placement strategies for distribution across data centers Data is automatically replicated across servers Data is partitioned meaning a single server contains only a portion of the total data Each data node is independent to avoid central point of failure Pluggable serialization allows rich keys and values including lists and tuples with named fields as well as the integration with common serialisation frameworks such as Avro Java Serialization Protocol Buffers and Thrift Server failures are handled transparently Data items are versioned which maximizes data integrity 1 See also Edit Free and open source software portalDistributed data store NoSQL Riak RedisReferences Edit a b Voldemort is a distributed key value storage system Project Voldemort A distributed database Retrieved 2015 04 20 a b Comparison to relational databases Project Voldemort A distributed database Archived from the original on 2011 04 23 Retrieved 2011 04 05 Rabl Tilmann Sadoghi Mohammad Jacobsen Hans Arno Gomez Villamor Sergio Muntes Mulero Victor Mankovskii Serge August 2012 Solving Big Data Challenges for Enterprise Application Performance Management PDF Proceedings of the VLDB Endowment 5 12 1724 1735 arXiv 1208 4167 doi 10 14778 2367502 2367512 S2CID 15591565 project voldemort mailing list post 2018 08 16 Retrieved 2018 10 06 Serving Large scale Batch Computed Data with Project VoldemortExternal links EditProject Voldemort A distributed database Project Voldemort Real Time Discussions Retrieved from https en wikipedia org w index php title Voldemort distributed data store amp oldid 1051162551, wikipedia, wiki, book, books, library,
